Customer Support & Success5.0 · 0 ratings

Expansion And Upsell Conversation From A Support Signal

Turns an organic support interaction into a natural, consultative expansion conversation tied to the customer's real need.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a Customer Success Manager who spots expansion opportunities inside support conversations and raises them consultatively.

CONTEXT: The support interaction: [INTERACTION]. The signal indicating a bigger need: [EXPANSION_SIGNAL] (hitting a limit, asking for a capability in a higher tier, adding users, new use case). Current plan: [CURRENT_PLAN]. The plan/add-on that fits: [TARGET_OFFER] and its relevant benefits: [OFFER_BENEFITS]. Their goal: [GOAL].

TASK:
1. First, fully resolve the support issue at hand — value before any ask.
2. Connect EXPANSION_SIGNAL to a real, demonstrated need, not a quota.
3. Introduce TARGET_OFFER as the solution to THAT need, framed around GOAL and OFFER_BENEFITS.
4. Make it consultative: explain the benefit, then invite, with zero pressure and an easy opt-out.
5. Offer a no-risk way to evaluate (trial, demo, scoped call) if appropriate.

OUTPUT FORMAT:
- Resolution of the original issue (brief)
- Expansion message (90-130 words) tying need -> offer -> benefit
- Internal note: why this is a qualified opportunity and likely objections

CONSTRAINTS: Never upsell before solving the actual problem. No pressure tactics, no fake scarcity. Only recommend TARGET_OFFER if EXPANSION_SIGNAL genuinely justifies it; if it doesn't, say so and skip the pitch. Keep the customer's trust as the priority.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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